Zobrazeno 1 - 10
of 421
pro vyhledávání: '"Sun, Defeng"'
This paper solves a fundamental open problem in variational analysis on the equivalence between the Aubin property and the strong regularity for nonlinear second-order cone programming (SOCP) at a locally optimal solution. We achieve this by introduc
Externí odkaz:
http://arxiv.org/abs/2406.13798
In this paper, we aim to accelerate a preconditioned alternating direction method of multipliers (pADMM), whose proximal terms are convex quadratic functions, for solving linearly constrained convex optimization problems. To achieve this, we first re
Externí odkaz:
http://arxiv.org/abs/2403.18618
Unsupervised feature selection has drawn wide attention in the era of big data since it is a primary technique for dimensionality reduction. However, many existing unsupervised feature selection models and solution methods were presented for the purp
Externí odkaz:
http://arxiv.org/abs/2403.16966
Recently, a quaternion tensor product named Qt-product was proposed, and then the singular value decomposition and the rank of a third-order quaternion tensor were given. From a more applicable perspective, we extend the Qt-product and propose a nove
Externí odkaz:
http://arxiv.org/abs/2403.16480
Autor:
Li, Xijun, Zhu, Fangzhou, Zhen, Hui-Ling, Luo, Weilin, Lu, Meng, Huang, Yimin, Fan, Zhenan, Zhou, Zirui, Kuang, Yufei, Wang, Zhihai, Geng, Zijie, Li, Yang, Liu, Haoyang, An, Zhiwu, Yang, Muming, Li, Jianshu, Wang, Jie, Yan, Junchi, Sun, Defeng, Zhong, Tao, Zhang, Yong, Zeng, Jia, Yuan, Mingxuan, Hao, Jianye, Yao, Jun, Mao, Kun
In an era of digital ubiquity, efficient resource management and decision-making are paramount across numerous industries. To this end, we present a comprehensive study on the integration of machine learning (ML) techniques into Huawei Cloud's OptVer
Externí odkaz:
http://arxiv.org/abs/2401.05960
In this paper, we propose an efficient sieving based secant method to address the computational challenges of solving sparse optimization problems with least-squares constraints. A level-set method has been introduced in [X. Li, D.F. Sun, and K.-C. T
Externí odkaz:
http://arxiv.org/abs/2308.07812
In this paper, we present a method to certify the approximation quality of a low rank tensor to a given third order symmetric tensor. Under mild assumptions, best low rank approximation is attained if a control parameter is zero or quantified quasi-o
Externí odkaz:
http://arxiv.org/abs/2307.10855
In this paper, we propose an adaptive sieving (AS) strategy for solving general sparse machine learning models by effectively exploring the intrinsic sparsity of the solutions, wherein only a sequence of reduced problems with much smaller sizes need
Externí odkaz:
http://arxiv.org/abs/2306.17369
The exclusive lasso (also known as elitist lasso) regularizer has become popular recently due to its superior performance on intra-group feature selection. Its complex nature poses difficulties for the computation of high-dimensional machine learning
Externí odkaz:
http://arxiv.org/abs/2306.14196
To ensure the system stability of the $\bf{\mathcal{H}_{2}}$-guaranteed cost optimal decentralized control problem (ODC), an approximate semidefinite programming (SDP) problem is formulated based on the sparsity of the gain matrix of the decentralize
Externí odkaz:
http://arxiv.org/abs/2304.11037